Defining the Dimensions of Diversity to Promote Inclusion in the Digital Era of Health Care: A Lexicon

The pandemic provided a stark reminder of the inequities faced by populations historically marginalized by the health care system and accelerated the adoption of digital health technologies to drive innovation. Digital health technologies' purported promises to reduce inefficiencies and costs, improve access and health outcomes, and empower patients add a new level of urgency to health equity. As conventional medicine shifts toward digital medicine, we have the opportunity to intentionally develop and deploy digital health technologies with an inclusion focus. The first step is ensuring that the multiple dimensions of diversity are captured. We propose a lexicon that encompasses elements critical for implementing an inclusive approach to advancing health care quality and health services research in the digital era.

A patient-centred conceptual model of nocturnal scratch and its impact in atopic dermatitis: A mixed-methods study supporting the development of novel digital measurements

Background

Emerging digital measures and clinical outcome assessments (COAs) leveraging digital health technologies (DHTs) could address the need for objective, quantitative measures of symptoms of atopic dermatitis (AD), such as nocturnal scratching. Development of such measures needs to be supported by evidence reflecting meaningfulness to patients.

Objectives

To assess nocturnal scratching as a concept of interest associated with meaningful aspects of health of patients with AD (adults and children); and to explore patient-centred considerations for novel COAs measuring nocturnal scratch using DHTs.

Methods

Phase 1 evaluated disease impacts on everyday life and the lived experience with nocturnal scratching through qualitative interviews of AD patients and caregivers. Phase 2 deployed a quantitative survey to a sample of AD patients as well as caregivers.

Results

Four cohorts with various AD severity levels participated in Phase 1: (1) adults with AD (n = 15), (2) their caregivers/spouses/partners (n = 6), (3) children with AD (n = 14), and (4) their adult caregivers (n = 14). Findings were used to develop a conceptual model for nocturnal scratching as a potential concept of interest. The Phase 2 survey was completed by 1349 of 27640 invited adults with AD and caregivers of children with AD. The most burdensome aspects of AD reported were itchy skin and scratching. Overall, ∼65% of participants reported nocturnal scratching ≥1 day/week, resulting in ∼1-1.4 h of sleep lost per night. In all, 85%-91% of respondents considered it at least somewhat valuable that a treatment reduces night-time scratching. About 50% reported willingness to use technology to this end and ∼25% were unsure.

Conclusion

Our results represented by the conceptual model confirm that nocturnal scratch is a concept of interest related to meaningful aspects of health for patients with AD and therefore is worth being captured as a distinct outcome for clinical and research purposes. DHTs are suitable tools presenting an important measurement opportunity to assess and evaluate occurrence, frequency, and other parameters of nocturnal scratching as a disease biomarker or COA of treatment efficacy.

Building the Business Case for an Inclusive Approach to Digital Health Measurement With a Web App (Market Opportunity Calculator): Instrument Development Study

BACKGROUND

The use of digital health measurement tools has grown substantially in recent years. However, there are concerns that the promised benefits from these products will not be shared equitably. Underserved populations, such as those with lower education and income, racial and ethnic minorities, and those with disabilities, may find such tools poorly suited for their needs. Because underserved populations shoulder a disproportionate share of the US disease burden, they also represent a substantial share of digital health companies' target markets. Incorporating inclusive principles into the product development process can help ensure that the resulting tools are broadly accessible and effective. In this context, inclusivity not only maximizes societal benefit but also leads to greater commercial success.

OBJECTIVE

A critical element in fostering inclusive product development is building the business case for why it is worthwhile. The Digital Health Measurement Collaborative Community (DATAcc) Market Opportunity Calculator was developed as an open-access resource to enable digital health measurement product developers to build a business case for incorporating inclusive practices into their research and development processes.

METHODS

The DATAcc Market Opportunity Calculator combines data on population demographics and disease prevalence and health status from the US Census Bureau and the US Centers for Disease Control and Prevention (CDC). Together, these data are used to calculate the share of US adults with specific conditions (eg, diabetes) falling into various population segments along key "inclusion vectors" (eg, race and ethnicity).

RESULTS

A free and open resource, the DATAcc Market Opportunity Calculator can be accessed from the DATAcc website. Users first select the target health condition addressed by their product, and then an inclusion vector to segment the patient population. The calculator displays each segment as a share of the overall US adult population and its share specifically among adults with the target condition, quantifying the importance of underserved patient segments to the target market. The calculator also estimates the value of improvements to product inclusivity by modeling the downstream impact on the accessible market size. For example, simplifying prompts on a hypertension-focused product to make it more accessible for adults with lower educational attainment is shown by the calculator to increase the target market by 2 million people and the total addressable market opportunity by US $200 million.

CONCLUSIONS

Digital health measurement is still in its infancy. Now is the time to establish a precedent for inclusive product development to maximize societal benefit and build sustainable commercial returns. The Market Opportunity Calculator can help build the business case for "why"-showing how inclusivity can translate to financial opportunity. Once the decision has been made to pursue inclusive design, other components of the broader DATAcc toolkit for inclusive product development can support the "how."

Rigorous and rapid evidence assessment in digital health with the evidence DEFINED framework

Dozens of frameworks have been proposed to assess evidence for digital health interventions (DHIs), but existing frameworks may not facilitate DHI evidence reviews that meet the needs of stakeholder organizations including payers, health systems, trade organizations, and others. These organizations may benefit from a DHI assessment framework that is both rigorous and rapid. Here we propose a framework to assess Evidence in Digital health for EFfectiveness of INterventions with Evaluative Depth (Evidence DEFINED). Designed for real-world use, the Evidence DEFINED Quick Start Guide may help streamline DHI assessment. A checklist is provided summarizing high-priority evidence considerations in digital health. Evidence-to-recommendation guidelines are proposed, specifying degrees of adoption that may be appropriate for a range of evidence quality levels. Evidence DEFINED differs from prior frameworks in its inclusion of unique elements designed for rigor and speed. Rigor is increased by addressing three gaps in prior frameworks. First, prior frameworks are not adapted adequately to address evidence considerations that are unique to digital health. Second, prior frameworks do not specify evidence quality criteria requiring increased vigilance for DHIs in the current regulatory context. Third, extant frameworks rarely leverage established, robust methodologies that were developed for non-digital interventions. Speed is achieved in the Evidence DEFINED Framework through screening optimization and deprioritization of steps that may have limited value. The primary goals of Evidence DEFINED are to a) facilitate standardized, rapid, rigorous DHI evidence assessment in organizations and b) guide digital health solutions providers who wish to generate evidence that drives DHI adoption.

Advancing Digital Health Innovation in Oncology: Priorities for High-Value Digital Transformation in Cancer Care

Although health care delivery is becoming increasingly digitized, driven by the pursuit of improved access, equity, efficiency, and effectiveness, progress does not appear to be equally distributed across therapeutic areas. Oncology is renowned for leading innovation in research and in care; digital pathology, digital radiology, real-world data, next-generation sequencing, patient-reported outcomes, and precision approaches driven by complex data and biomarkers are hallmarks of the field. However, remote patient monitoring, decentralized approaches to care and research, "hospital at home," and machine learning techniques have yet to be broadly deployed to improve cancer care. In response, the Digital Medicine Society and Moffitt Cancer Center convened a multistakeholder roundtable discussion to bring together leading experts in cancer care and digital innovation. This viewpoint highlights the findings from these discussions, in which experts agreed that digital innovation is lagging in oncology relative to other therapeutic areas. It reports that this lag is most likely attributed to poor articulation of the challenges in cancer care and research best suited to digital solutions, lack of incentives and support, and missing standardized infrastructure to implement digital innovations. It concludes with suggestions for actions needed to bring the promise of digitization to cancer care to improve lives.

Defining digital measurement of scratching during sleep, or “Nocturnal Scratch”: A review of the literature (Preprint)

BACKGROUND

Digital sensing solutions represent a convenient, objective, relatively inexpensive method that could be leveraged for assessing symptoms of various health conditions. Recent progress in the capabilities of digital sensing products has targeted the measurement of scratching during sleep, traditionally referred to as nocturnal scratching, in patients with atopic dermatitis or other skin conditions. Many solutions measuring nocturnal scratch have been developed; however, a lack of efforts toward standardization of the measure's definition and contextualization of scratching during sleep hampers the ability to compare different technologies for this purpose.

OBJECTIVE

We aimed to address this gap and bring forth unified measurement definitions for nocturnal scratch.

METHODS

We performed a narrative literature review of definitions of scratching in patients with skin inflammation and a targeted literature review of sleep in the context of the period during which such scratching occurred. Both searches were limited to English language studies in humans. The extracted data were synthesized into themes based on study characteristics: scratch as a behavior, other characterization of the scratching movement, and measurement parameters for both scratch and sleep. We then developed ontologies for the digital measurement of sleep scratching.

RESULTS

In all, 29 studies defined inflammation-related scratching between 1996 and 2021. When cross-referenced with the results of search terms describing the sleep period, only 2 of these scratch-related papers also described sleep-related variables. From these search results, we developed an evidence-based and patient-centric definition of nocturnal scratch: an action of rhythmic and repetitive skin contact movement performed during a delimited time period of intended and actual sleep that is not restricted to any specific time of the day or night. Based on the measurement properties identified in the searches, we developed ontologies of relevant concepts that can be used as a starting point to develop standardized outcome measures of scratching during sleep in patients with inflammatory skin conditions.

CONCLUSIONS

This work is intended to serve as a foundation for the future development of unified and well-described digital health technologies measuring nocturnal scratching and should enable better communication and sharing of results between various stakeholders taking part in research in atopic dermatitis and other inflammatory skin conditions.

Sensor Data Integration: A New Cross-Industry Collaboration to Articulate Value, Define Needs, and Advance a Framework for Best Practices

Data integration, the processes by which data are aggregated, combined, and made available for use, has been key to the development and growth of many technological solutions. In health care, we are experiencing a revolution in the use of sensors to collect data on patient behaviors and experiences. Yet, the potential of this data to transform health outcomes is being held back. Deficits in standards, lexicons, data rights, permissioning, and security have been well documented, less so the cultural adoption of sensor data integration as a priority for large-scale deployment and impact on patient lives. The use and reuse of trustworthy data to make better and faster decisions across drug development and care delivery will require an understanding of all stakeholder needs and best practices to ensure these needs are met. The Digital Medicine Society is launching a new multistakeholder Sensor Data Integration Tour of Duty to address these challenges and more, providing a clear direction on how sensor data can fulfill its potential to enhance patient lives.

Recent Academic Research on Clinically Relevant Digital Measures: Systematic Review

Background

Digital clinical measures collected via various digital sensing technologies such as smartphones, smartwatches, wearables, ingestibles, and implantables are increasingly used by individuals and clinicians to capture health outcomes or behavioral and physiological characteristics of individuals. Although academia is taking an active role in evaluating digital sensing products, academic contributions to advancing the safe, effective, ethical, and equitable use of digital clinical measures are poorly characterized.

Objective

We performed a systematic review to characterize the nature of academic research on digital clinical measures and to compare and contrast the types of sensors used and the sources of funding support for specific subareas of this research.

Methods

We conducted a PubMed search using a range of search terms to retrieve peer-reviewed articles reporting US-led academic research on digital clinical measures between January 2019 and February 2021. We screened each publication against specific inclusion and exclusion criteria. We then identified and categorized research studies based on the types of academic research, sensors used, and funding sources. Finally, we compared and contrasted the funding support for these specific subareas of research and sensor types.

Results

The search retrieved 4240 articles of interest. Following the screening, 295 articles remained for data extraction and categorization. The top five research subareas included operations research (research analysis; n=225, 76%), analytical validation (n=173, 59%), usability and utility (data visualization; n=123, 42%), verification (n=93, 32%), and clinical validation (n=83, 28%). The three most underrepresented areas of research into digital clinical measures were ethics (n=0, 0%), security (n=1, 0.5%), and data rights and governance (n=1, 0.5%). Movement and activity trackers were the most commonly studied sensor type, and physiological (mechanical) sensors were the least frequently studied. We found that government agencies are providing the most funding for research on digital clinical measures (n=192, 65%), followed by independent foundations (n=109, 37%) and industries (n=56, 19%), with the remaining 12% (n=36) of these studies completely unfunded.

Conclusions

Specific subareas of academic research related to digital clinical measures are not keeping pace with the rapid expansion and adoption of digital sensing products. An integrated and coordinated effort is required across academia, academic partners, and academic funders to establish the field of digital clinical measures as an evidence-based field worthy of our trust.

EVIDENCE Publication Checklist for Studies Evaluating Connected Sensor Technologies: Explanation and Elaboration

The EVIDENCE (EValuatIng connecteD sENsor teChnologiEs) checklist was developed by a multidisciplinary group of content experts convened by the Digital Medicine Society, representing the clinical sciences, data management, technology development, and biostatistics. The aim of EVIDENCE is to promote high quality reporting in studies where the primary objective is an evaluation of a digital measurement product or its constituent parts. Here we use the terms digital measurement product and connected sensor technology interchangeably to refer to tools that process data captured by mobile sensors using algorithms to generate measures of behavioral and/or physiological function. EVIDENCE is applicable to 5 types of evaluations: (1) proof of concept; (2) verification, (3) analytical validation, and (4) clinical validation as defined by the V3 framework; and (5) utility and usability assessments. Using EVIDENCE, those preparing, reading, or reviewing studies evaluating digital measurement products will be better equipped to distinguish necessary reporting requirements to drive high-quality research. With broad adoption, the EVIDENCE checklist will serve as a much-needed guide to raise the bar for quality reporting in published literature evaluating digital measurements products.

Evaluation, Acceptance, and Qualification of Digital Measures: From Proof of Concept to Endpoint

To support the successful adoption of digital measures into internal decision making and evidence generation for medical product development, we present a unified lexicon to aid communication throughout this process, and highlight key concepts including the critical role of participant engagement in development of digital measures. We detail the steps of bringing a successful proof of concept to scale, focusing on key decisions in the development of a new digital measure: asking the right question, optimized approaches to evaluating new measures, and whether and how to pursue qualification or acceptance. Building on the V3 framework for establishing verification and analytical and clinical validation, we discuss strategic and practical considerations for collecting this evidence, illustrated with concrete examples of trailblazing digital measures in the field.

Defining and Developing the Workforce Needed for Success in the Digital Era of Medicine

Artificial intelligence offers the promise of transforming biomedical research and helping clinicians put the "care" back in healthcare. Digital medicine is on its way to becoming just plain medicine. But who will digitize how we define health and disease? And who will deploy this knowledge to improve the lives of patients that medicine - and digital medicine - exists to serve? Here we define the emerging field of digital medicine and identify the disciplines and skills needed for success. We examine the current and projected skills gaps. We also consider the impact of the culture clash that occurs at the intersection of healthcare and technology, and the lack of diversity in the workforce of both of these fields. We conclude by describing the requirements for the skills pivot needed to ensure that the digital transformation of healthcare is successful: (1) big tent thinking to recognize the critical importance of new technical skills alongside more traditional clinical disciplines, (2) the integration of clinical and technical skill sets within educational curricula, companies, and professional institutions, and (3) a commitment to diversity that goes beyond lip service.

Precompetitive Consensus Building to Facilitate the Use of Digital Health Technologies to Support Parkinson Disease Drug Development through Regulatory Science

Innovative tools are urgently needed to accelerate the evaluation and subsequent approval of novel treatments that may slow, halt, or reverse the relentless progression of Parkinson disease (PD). Therapies that intervene early in the disease continuum are a priority for the many candidates in the drug development pipeline. There is a paucity of sensitive and objective, yet clinically interpretable, measures that can capture meaningful aspects of the disease. This poses a major challenge for the development of new therapies and is compounded by the considerable heterogeneity in clinical manifestations across patients and the fluctuating nature of many signs and symptoms of PD. Digital health technologies (DHT), such as smartphone applications, wearable sensors, and digital diaries, have the potential to address many of these gaps by enabling the objective, remote, and frequent measurement of PD signs and symptoms in natural living environments. The current climate of the COVID-19 pandemic creates a heightened sense of urgency for effective implementation of such strategies. In order for these technologies to be adopted in drug development studies, a regulatory-aligned consensus on best practices in implementing appropriate technologies, including the collection, processing, and interpretation of digital sensor data, is required. A growing number of collaborative initiatives are being launched to identify effective ways to advance the use of DHT in PD clinical trials. The Critical Path for Parkinson's Consortium of the Critical Path Institute is highlighted as a case example where stakeholders collectively engaged regulatory agencies on the effective use of DHT in PD clinical trials. Global regulatory agencies, including the US Food and Drug Administration and the European Medicines Agency, are encouraging the efficiencies of data-driven engagements through multistakeholder consortia. To this end, we review how the advancement of DHT can be most effectively achieved by aligning knowledge, expertise, and data sharing in ways that maximize efficiencies.

Underuse of oral anticoagulants in privately insured patients with atrial fibrillation: A population being targeted by the IMplementation of a randomized controlled trial to imProve treatment with oral AntiCoagulanTs in patients with Atrial Fibrillation (IMPACT-AFib)

BACKGROUND

Many studies showing underuse of oral anticoagulants (OACs) in patients with atrial fibrillation (AF) predated the advent of the non-vitamin K antagonist OACs. We retrospectively examined use of OACs in a large commercially insured population.

METHODS

Administrative claims data from 4 research partners participating in FDA-Catalyst, a program of the Sentinel Initiative, were queried in September 2017. Patients were included if they were ≥30 years old with ≥365 days of medical/pharmacy coverage, and had ≥2 diagnosis codes for AF, a CHA₂DS₂-VASc score ≥2, absence of contraindications to OAC use, and no evidence of OAC use in the 365 days before the index AF diagnosis. The main outcome measures of the current analysis were rates of OAC use in the prior 12 months of cohort identification and factors associated with non-use.

RESULTS

A total of 197,806 AF patients met the eligibility criteria prior to assessment of OAC treatment. Of these, 179,580 (91%) patients were ≥65 years old and 73,286 (37%) patients were ≥80 years old. Half of the patients (98,903) were randomized to the early intervention arm in the IMPACT-AFib trial and constitute the cohort for this analysis. Of these, 32,295 (33%) had no evidence of OAC use in the prior 12 months. Compared with patients with evidence of OAC use in the prior 12 months, patients without OAC use were more likely to be ≥80 years old, women, and have a history of anemia (51% vs 47%) and less likely to have diabetes (41% vs 44%), history of stroke or TIA (15% vs 19%), and history of heart failure (39% vs 48%).

CONCLUSIONS

Despite a high risk of stroke, one-third of privately insured patients with AF and no obvious contraindications to an OAC were not treated with an OAC. There is an unmet need for evidence-based interventions that could lead to greater use of OACs in patients with AF at risk for stroke.

Bystander Ethics and Good Samaritanism: A Paradox for Learning Health Organizations

In 2012, a U.S. Institute of Medicine report called for a different approach to health care: "Left unchanged, health care will continue to underperform; cause unnecessary harm; and strain national, state, and family budgets." The answer, they suggested, would be a "continuously learning" health system. Ethicists and researchers urged the creation of "learning health organizations" that would integrate knowledge from patient-care data to continuously improve the quality of care. Our experience with an ongoing research study on atrial fibrillation-a trial known as IMPACT-AFib-gave us some insight into one of the challenges that will have to be dealt with in creating these organizations. Although the proposed educational intervention study placed no restrictions on what providers and health plans could do, the oversight team argued that the ethical principle of beneficence did not allow the researchers to be "bystanders" in relation to a control group receiving suboptimal care. In response, the researchers designed a "workaround" that allowed the project to go forward. We believe the experience suggests that what we call "bystander ethics" will create challenges for the kinds of quality improvement research that LHOs are designed to do.

Digital Measures That Matter to Patients: A Framework to Guide the Selection and Development of Digital Measures of Health

Background

With the rise of connected sensor technologies, there are seemingly endless possibilities for new ways to measure health. These technologies offer researchers and clinicians opportunities to go beyond brief snapshots of data captured by traditional in-clinic assessments, to redefine health and disease. Given the myriad opportunities for measurement, how do research or clinical teams know what they should be measuring? Patient engagement, early and often, is paramount to thoughtfully selecting what is most important. Regulators encourage stakeholders to have a patient focus but actionable steps for continuous engagement are not well defined. Without patient-focused measurement, stakeholders risk entrenching digital versions of poor traditional assessments and proliferating low-value tools that are ineffective, burdensome, and reduce both quality and efficiency in clinical care and research.

Summary

This article synthesizes and defines a sequential framework of core principles for selecting and developing measurements in research and clinical care that are meaningful for patients. We propose next steps to drive forward the science of high-quality patient engagement in support of measures of health that matter in the era of digital medicine.

Key Messages

All measures of health should be meaningful, regardless of the product's regulatory classification, type of measure, or context of use. To evaluate meaningfulness of signals derived from digital sensors, the following four-level framework is useful: Meaningful Aspect of Health, Concept of Interest, Outcome to be measured, and Endpoint (exclusive to research). Incorporating patient input is a dynamic process that requires more than a single, transactional touch point but rather should be conducted continuously throughout the measurement selection process. We recommend that developers, clinicians, and researchers reevaluate processes for more continuous patient engagement in the development, deployment, and interpretation of digital measures of health.

BioMeT and Algorithm Challenges: A Proposed Digital Standardized Evaluation Framework

Technology is advancing at an extraordinary rate. Continuous flows of novel data are being generated with the potential to revolutionize how we better identify, treat, manage, and prevent disease across therapeutic areas. However, lack of security of confidence in digital health technologies is hampering adoption, particularly for biometric monitoring technologies (BioMeTs) where frontline healthcare professionals are struggling to determine which BioMeTs are fit-for-purpose and in which context. Here, we discuss the challenges to adoption and offer pragmatic guidance regarding BioMeTs, cumulating in a proposed framework to advance their development and deployment in healthcare, health research, and health promotion. Furthermore, the framework proposes a process to establish an audit trail of BioMeTs (hardware and algorithms), to instill trust amongst multidisciplinary users.

Verification, analytical validation, and clinical validation (V3): the foundation of determining fit-for-purpose for Biometric Monitoring Technologies (BioMeTs)

Digital medicine is an interdisciplinary field, drawing together stakeholders with expertize in engineering, manufacturing, clinical science, data science, biostatistics, regulatory science, ethics, patient advocacy, and healthcare policy, to name a few. Although this diversity is undoubtedly valuable, it can lead to confusion regarding terminology and best practices. There are many instances, as we detail in this paper, where a single term is used by different groups to mean different things, as well as cases where multiple terms are used to describe essentially the same concept. Our intent is to clarify core terminology and best practices for the evaluation of Biometric Monitoring Technologies (BioMeTs), without unnecessarily introducing new terms. We focus on the evaluation of BioMeTs as fit-for-purpose for use in clinical trials. However, our intent is for this framework to be instructional to all users of digital measurement tools, regardless of setting or intended use. We propose and describe a three-component framework intended to provide a foundational evaluation framework for BioMeTs. This framework includes (1) verification, (2) analytical validation, and (3) clinical validation. We aim for this common vocabulary to enable more effective communication and collaboration, generate a common and meaningful evidence base for BioMeTs, and improve the accessibility of the digital medicine field.

Considerations for development of an evidence dossier to support the use of mobile sensor technology for clinical outcome assessments in clinical trials

BACKGROUND

Mobile sensors offer enormous potential for the collection of informative clinical endpoints in clinical trials to support regulatory decision making and product labelling. There are currently no specific guidelines on the information needed to enable regulators to review and accept proposed endpoints derived from mobile sensors for use in drug development trials.

OBJECTIVE

The purpose of this working group report is to recommend the structure and content of an evidence dossier intended to support whether a clinical endpoint derived from mobile sensor data is fit-for-purpose for use in regulatory submissions for drug approvals.

EVIDENCE DOSSIER

The structure and content of a dossier to provide evidence supporting the use of a sensor-derived clinical endpoint is described. Sections include clinical endpoint definition and positioning, the concept of interest, the context of use, clinical validation and interpretation, study implementation, and analytical validity with sensor performance verification in support of the selected sensor.

CONCLUSIONS

In the absence of definitive regulatory guidance, this report provides a considered approach to compiling a comprehensive body of evidence to justify acceptance of mobile sensors for support of new drug applications.

Continuous Sound Collection Using Smartphones and Machine Learning to Measure Cough

Background

Despite the efforts of research groups to develop and implement at least partial automation, cough counting remains impractical. Analysis of 24-h cough frequency is an established regulatory endpoint which, if addressed in an automated manner, has the potential to ease cough symptom evaluation over multiple 24-h periods in a patient-centric way, supporting the development of novel treatments for chronic cough, an unmet clinical need.

Objectives

In light of recent technological advancements, we propose a system based on the use of smartphones for objective continuous sound collection, suitable for automated cough detection and analysis. Two capabilities were identified as necessary for naturalistic cough assessment: (1) recording sound in a continuous manner (sound collection), and (2) detection of coughs from the recorded sound (cough detection).

Methods

This work did not involve any human subject testing or trials. For sound collection, we designed, built, and verified technical parameters of a smartphone application for sound collection. Our cough detection work describes the development of a mathematical model for sound analysis and cough identification. Performance of the model was compared to previously published results of commercially available solutions and to human raters. The compared solutions use the following methods to automatically or semi-automatically assess cough: 24-h sound recording with an ambulatory device with multiple microphones, automatic silence removal, and manual recording review for cough count.

Results

Sound collection: the application demonstrated the ability to continuously record sounds using the phone's internal microphone; the technical verification informed the configuration of the technical and user experience parameters. Cough detection: our cough recognition sensitivity to cough as determined by human listeners was 90 at 99.5% specificity preset and 75 at 99.9% specificity preset for a dataset created from publicly available data.

Conclusions

Sound collection: the application reliably collects sound data and uploads them securely to a remote server for subsequent analysis; the developed sound data collection application is a critical first step toward future incorporation in clinical trials. Cough detection: initial experiments with cough detection techniques yielded encouraging results for application to patient-collected data from future studies.

Advancing the Use of Mobile Technologies in Clinical Trials: Recommendations from the Clinical Trials Transformation Initiative

Mobile technologies offer the potential to reduce the costs of conducting clinical trials by collecting high-quality information on health outcomes in real-world settings that are relevant to patients and clinicians. However, widespread use of mobile technologies in clinical trials has been impeded by their perceived challenges. To advance solutions to these challenges, the Clinical Trials Transformation Initiative (CTTI) has issued best practices and realistic approaches that clinical trial sponsors can now use. These include CTTI recommendations on technology selection; data collection, analysis, and interpretation; data management; protocol design and execution; and US Food and Drug Administration submission and inspection. The scientific principles underpinning the clinical trials enterprise continue to apply to studies using mobile technologies. These recommendations provide a framework for including mobile technologies in clinical trials that can lead to more efficient assessment of new therapies for patients.

A systematic review of feasibility studies promoting the use of mobile technologies in clinical research

Mobile technologies, such as smart phone applications, wearables, ingestibles, and implantables, are increasingly used in clinical research to capture study endpoints. On behalf of the Clinical Trials Transformation Initiative, we aimed to conduct a systematic scoping review and compile a database summarizing pilot studies addressing mobile technology sensor performance, algorithm development, software performance, and/or operational feasibility, in order to provide a resource for guiding decisions about which technology is most suitable for a particular trial. Our systematic search identified 275 publications meeting inclusion criteria. From these papers, we extracted data including the medical condition, concept of interest captured by the mobile technology, outcomes captured by the digital measurement, and details regarding the sensors, algorithms, and study sample. Sixty-seven percent of the technologies identified were wearable sensors, with the remainder including tablets, smartphones, implanted sensors, and cameras. We noted substantial variability in terms of reporting completeness and terminology used. The data have been compiled into an online database maintained by the Clinical Trials Transformation Initiative that can be filtered and searched electronically, enabling a user to find information most relevant to their work. Our long-term goal is to maintain and update the online database, in order to promote standardization of methods and reporting, encourage collaboration, and avoid redundant studies, thereby contributing to the design and implementation of efficient, high-quality trials.

The Clinical Trials Transformation Initiative: Methodology supporting the mission

The mission of the Clinical Trials Transformation Initiative, a public-private partnership co-founded by the U.S. Food and Drug Administration and Duke University, is to develop and drive adoption of practices that will increase the quality and efficiency of clinical trials. The Clinical Trials Transformation Initiative works collaboratively with key stakeholders, implements "fit-for-purpose" evidence-gathering projects, and develops actionable recommendations and tools to address the challenges faced by the clinical trials enterprise. In pursuit of its mission, The Clinical Trials Transformation Initiative follows an innovative and collaborative, five-step methodology: (1) state the problem and identify impediments to research, (2) gather evidence to identify gaps and barriers, (3) explore results by analyzing and interpreting findings, (4) finalize solutions by developing recommendations and tools, and (5) drive adoption through disseminating and implementing recommendations and tools. This article describes each step of the Clinical Trials Transformation Initiative's methodology, with a specific focus on describing the evidence-gathering activities.

Digital Medicine: A Primer on Measurement

Technology is changing how we practice medicine. Sensors and wearables are getting smaller and cheaper, and algorithms are becoming powerful enough to predict medical outcomes. Yet despite rapid advances, healthcare lags behind other industries in truly putting these technologies to use. A major barrier to entry is the cross-disciplinary approach required to create such tools, requiring knowledge from many people across many fields. We aim to drive the field forward by unpacking that barrier, providing a brief introduction to core concepts and terms that define digital medicine. Specifically, we contrast "clinical research" versus routine "clinical care," outlining the security, ethical, regulatory, and legal issues developers must consider as digital medicine products go to market. We classify types of digital measurements and how to use and validate these measures in different settings. To make this resource engaging and accessible, we have included illustrations and figures throughout that we hope readers will borrow from liberally. This primer is the first in a series that will accelerate the safe and effective advancement of the field of digital medicine.

FDA-Catalyst-Using FDA's Sentinel Initiative for large-scale pragmatic randomized trials: Approach and lessons learned during the planning phase of the first trial

BACKGROUND

The US Food and Drug Administration's Sentinel Initiative is well positioned to support pragmatic clinical trials. FDA-Catalyst combines direct contact with health plan members and/or providers with data in the Sentinel infrastructure. Here, we describe the rationale, feasibility analyses, and lessons learned from the planning phase of the first large pragmatic trial conducted using the Sentinel Initiative's delivery system capabilities-IMplementation of a randomized controlled trial to imProve treatment with oral AntiCoagulanTs in patients with Atrial Fibrillation (the IMPACT-AFib trial).

METHODS

During the planning phase, we convened representatives from five commercial health plans, FDA, study coordinating centers, and a patient representative for protocol development, institutional review board preparation, and other activities. Administrative claims data from the plans were included in a retrospective cohort analysis to assess sample size for the trial. Members ≥30 years old with ≥365 days of medical/pharmacy coverage, ≥2 diagnosis codes for atrial fibrillation, a guideline-based indication for oral anticoagulant use for stroke prevention, and no evidence of oral anticoagulant use in the 365 days prior to the index atrial fibrillation diagnosis in 2013 were included. Exclusions for the analysis included other conditions requiring anticoagulation, history of intracranial hemorrhage, and gastrointestinal bleed. We calculated rates of oral anticoagulant use, transient ischemic attack or stroke, and bleeding in the 365 days following the index atrial fibrillation diagnosis.

RESULTS

A total of 44,786 members with atrial fibrillation with no evidence of recent oral anticoagulant use were identified. In total, 87% (n = 38,759) were classified as having a guideline-based indication for oral anticoagulants. Of those, 33% (n = 12,867) had a new oral anticoagulant dispensed during the following year, 15% (n = 5917) were hospitalized for stroke or transient ischemic attack, and 9% (n = 3469) for bleeding events. This information was used to develop the trial protocol including sample size, power calculations, and level of randomization.

CONCLUSION

Sentinel infrastructure generated preliminary data that supported planning and implementation of a large pragmatic trial embedded in health plans. This planning identified unanticipated challenges that must be addressed in similar trials.

Use of Mobile Devices to Measure Outcomes in Clinical Research, 2010-2016: A Systematic Literature Review

Background

The use of mobile devices in clinical research has advanced substantially in recent years due to the rapid pace of technology development. With an overall aim of informing the future use of mobile devices in interventional clinical research to measure primary outcomes, we conducted a systematic review of the use of and clinical outcomes measured by mobile devices (mobile outcomes) in observational and interventional clinical research.

Method

We conducted a PubMed search using a range of search terms to retrieve peer-reviewed articles on clinical research published between January 2010 and May 2016 in which mobile devices were used to measure study outcomes. We screened each publication for specific inclusion and exclusion criteria. We then identified and qualitatively summarized the use of mobile outcome assessments in clinical research, including the type and design of the study, therapeutic focus, type of mobile device(s) used, and specific mobile outcomes reported.

Results

The search retrieved 2,530 potential articles of interest. After screening, 88 publications remained. Twenty-five percent of the publications (n = 22) described mobile outcomes used in interventional research, and the rest (n = 66) described observational clinical research. Thirteen therapeutic areas were represented. Five categories of mobile devices were identified: (1) inertial sensors, (2) biosensors, (3) pressure sensors and walkways, (4) medication adherence monitors, and (5) location monitors; inertial sensors/accelerometers were most common (reported in 86% of the publications). Among the variety of mobile outcomes, various assessments of physical activity were most common (reported in 74% of the publications). Other mobile outcomes included assessments of sleep, mobility, and pill adherence, as well as biomarkers assessed using a mobile device, including cardiac measures, glucose, gastric reflux, respiratory measures, and intensity of head-related injury.

Conclusion

Mobile devices are being widely used in clinical research to assess outcomes, although their use in interventional research to assess therapeutic effectiveness is limited. For mobile devices to be used more frequently in pivotal interventional research – such as trials informing regulatory decision-making – more focus should be placed on: (1) consolidating the evidence supporting the clinical meaningfulness of specific mobile outcomes, and (2) standardizing the use of mobile devices in clinical research to measure specific mobile outcomes (e.g., data capture frequencies, placement of device). To that aim, this manuscript offers a broad overview of the various mobile outcome assessments currently used in observational and interventional research, and categorizes and consolidates this information for researchers interested in using mobile devices to assess outcomes in interventional research.

Improving Conduct and Feasibility of Clinical Trials to Evaluate Antibacterial Drugs to Treat Hospital-Acquired Bacterial Pneumonia and Ventilator-Associated Bacterial Pneumonia: Recommendations of the Clinical Trials Transformation Initiative Antibacterial Drug Development Project Team

BACKGROUND

The etiology of hospital-acquired or ventilator-associated bacterial pneumonia (HABP/VABP) is often multidrug-resistant infections. The evaluation of new antibacterial drugs for efficacy in this population is important, as many antibacterial drugs have demonstrated limitations when studied in this population. HABP/VABP trials are expensive and challenging to conduct due to protocol complexity and low patient enrollment, among other factors. The Clinical Trials Transformation Initiative (CTTI) seeks to advance antibacterial drug development by streamlining HABP/VABP clinical trials to improve efficiency and feasibility while maintaining ethical rigor, patient safety, information value, and scientific validity.

METHODS

In 2013, CTTI engaged a multidisciplinary group of experts to discuss challenges impeding the conduct of HABP/VABP trials. Separate workstreams identified challenges associated with HABP/VABP protocol complexity. The Project Team developed potential solutions to streamline HABP/VABP trials using a Quality by Design approach.

RESULTS

CTTI recommendations focus on 4 key areas to improve HABP/VABP trials: informed consent processes/practices, protocol design, choice of an institutional review board (IRB), and trial outcomes. Informed consent processes should include legally authorized representatives. Protocol design decisions should focus on eligibility criteria, prestudy antibacterial therapy considerations, use of new diagnostics, and sample size. CTTI recommends that sponsors use a central IRB and discuss trial endpoints with regulators, including defining a clinical failure and evaluating the impact of concomitant antibacterial drugs.

CONCLUSIONS

Streamlining HABP/VABP trials by addressing key protocol elements can improve trial startup and patient recruitment/retention, reduce trial complexity and costs, and ensure patient safety while advancing antibacterial drug development.

Remote and interdisciplinary research in surgical knowledge production

BACKGROUND

Surgical knowledge production has changed dramatically in the last 30 y, moving away from investigations by individual surgeon researchers and toward remote and interdisciplinary research. We investigated how surgeons make decisions about engaging in research and identify motivators, facilitators, and barriers to conducting research in an increasingly challenging environment.

MATERIALS AND METHODS

We performed a qualitative analysis of semistructured interviews with surgeons from academic medical centers across the United States. We asked participants to describe their experiences and opinions regarding remote and interdisciplinary collaborations.

RESULTS

Of 64 surgeon researchers invited, 21 (33%) agreed and participated in semistructured interviews. Each interview lasted an average (standard deviation) of 29 min (12). Surgeons were motivated by both internal and external factors, including some that might be identified as barriers. The internal desire to improve care and the need for collaboration to address increasingly complex questions requiring larger samples sizes emerged as most significant to interview participants. Social networks were identified as the dominant facilitator of multisite research, with technology playing a supporting role. Barriers to remote and interdisciplinary research ranged from individual, "micro" level barriers, through structural barriers that include institutional level challenges and competing priorities, to macrolevel system and policy-level barriers.

CONCLUSIONS

Surgeons clearly recognize the importance of high-quality research aligned with current paradigms of clinical care and are using remote and interdisciplinary collaboration to improve the quality of the science they produce and align their work with the demand for increasingly high levels of evidence.

Clinical, patient experience and cost impacts of performing active surveillance on known methicillin-resistant Staphylococcus aureus positive patients admitted to medical-surgical units

BACKGROUND

There is a large and growing body of evidence that methicillin-resistant Staphylococcus aureus (MRSA) screening programs are cost effective, but such screening represents a significant cost burden for hospitals. This study investigates the clinical, patient experience and cost impacts of performing active surveillance on known methicillin-resistant S aureus positive (MRSA+) patients admitted to 7 medical-surgical units of a large regional hospital, specifically to allow discontinuation of contact isolation.

METHODS

We conducted mixed-methods retrospective evaluation of a process improvement project that screened admitted patients with known MRSA+ status for continued MRSA colonization.

RESULTS

Of those eligible patients on our institution's MRSA+ list who did complete testing, 80.2% (130/162) were found to be no longer colonized, and only 19.8% (32/162) were still colonized. Forty-one percent (13/32) of interviewed patients in contact isolation for MRSA reported that isolation had affected their hospital stay, and 28% (9/32) of patients reported emotional distress resulting from their isolation. Total cost savings of the program are estimated at $101,230 per year across the 7 study units.

CONCLUSION

Our findings provide supporting evidence that a screening program targeting patients with a history of MRSA who would otherwise be placed in isolation has the potential to improve outcomes and patient experience and reduce costs.

Methodological recommendations for comparative research on the treatment of chronic wounds

OBJECTIVE

To provide specific recommendations to product developers and clinical researchers on the design of comparative effectiveness studies for the treatment of chronic wounds, specifically those pertaining to arterial and venous-disease related ulcers, diabetic foot ulcers, pressure ulcers and burn wounds.

METHOD

The recommendations were developed based on a process defined by the Center for Medical Technology Policy (CMTP). After selecting the subject area, semi-structured phone interviews were conducted by one of the authors (SSS) with representatives of payers, manufacturers, clinicians, clinician/researchers and patient advocates. Next, a broad range of stakeholders participated in a meeting convened by CMTP to determine their needs. A technical working group comprising key stakeholders then participated in clarifying recommendations developed by CMTP staff and adding important considerations for their implementation. The resulting draft document was finalised based on public and solicited comment from individual manufacturers; a consortium of product developers and manufacturers; and an alliance of physicians, providers, manufacturers and patient organisations. This article is a summary of the full effectiveness guidance document.

RESULTS

To address the needs of patients, clinicians, guideline developers, payers and other post-regulatory decision makers, this work makes ten recommendations to guide comparative effectiveness research for chronic wound care. These recommendations fall into four categories: study design, population, comparators and outcomes.

CONCLUSION

This paper suggests that using the recommendations outlined to conduct comparative effectiveness research on treatments for chronic wound therapies would facilitate trials that provide patients, clinicians, and payers with the information they need to make optimal treatment decisions. These recommendations focus on design changes that would have the largest impact in improving the usability of the results by decision makers and provide specific guidance on the design of prospective studies intended to inform decision making by patients, clinicians and payers.

DECLARATION OF INTEREST

There were no external sources of funding for these recommendations. The Value Institute and the Center for Medical Technology Policy (CMTP) are both private, non-profit organisations. The authors have no financial, commercial or social conflicts of interest to declare with respect to the article or its content.